EP2509500B1 - Evaluation de debit sanguin collateral - Google Patents

Evaluation de debit sanguin collateral Download PDF

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Publication number
EP2509500B1
EP2509500B1 EP10796141.9A EP10796141A EP2509500B1 EP 2509500 B1 EP2509500 B1 EP 2509500B1 EP 10796141 A EP10796141 A EP 10796141A EP 2509500 B1 EP2509500 B1 EP 2509500B1
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Prior art keywords
inflow
healthy tissue
perfusion
interest
healthy
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German (de)
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EP2509500A1 (fr
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Joerg Bredno
Max Wintermark
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Koninklijke Philips NV
University of California
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Koninklijke Philips NV
University of California
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    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/48Diagnostic techniques
    • A61B6/481Diagnostic techniques involving the use of contrast agents
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00Measuring for diagnostic purposes; Identification of persons
    • A61B5/02Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/02028Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/50Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
    • A61B6/507Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for determination of haemodynamic parameters, e.g. perfusion CT
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/06Measuring blood flow
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R33/00Arrangements or instruments for measuring magnetic variables
    • G01R33/20Arrangements or instruments for measuring magnetic variables involving magnetic resonance
    • G01R33/44Arrangements or instruments for measuring magnetic variables involving magnetic resonance using nuclear magnetic resonance [NMR]
    • G01R33/48NMR imaging systems
    • G01R33/54Signal processing systems, e.g. using pulse sequences ; Generation or control of pulse sequences; Operator console
    • G01R33/56Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution
    • G01R33/563Image enhancement or correction, e.g. subtraction or averaging techniques, e.g. improvement of signal-to-noise ratio and resolution of moving material, e.g. flow contrast angiography
    • G01R33/56366Perfusion imaging

Definitions

  • the following generally relates to assessing collateral blood flow in tissue of interest based on imaging data from one or more imaging modalities such as computed tomography (CT), magnetic resonance (MR), positron emission tomography (PET), single photon emission computed tomography (SPECT), x-ray radiography (X-Ray), ultrasound (US), and/or other imaging modalities.
  • CT computed tomography
  • MR magnetic resonance
  • PET positron emission tomography
  • SPECT single photon emission computed tomography
  • X-Ray x-ray radiography
  • US ultrasound
  • Collateral blood flow which is blood flow through smaller arterial pathways that connect neighboring regions primarily supplied by different major arteries, has been identified as information that can be used to predict acute stroke outcome and to assess risk for patients with carotid stenosis.
  • a static rating for collateral flow can be determined in perfusion territories with a completely occluded major feeding artery.
  • the amount of contrast agent visible in vessels behind a complete occlusion provides information on collateral inflow into this territory. More particularly, a presence of contrast agent downstream from a complete occlusion indicates collateral flow, and an absence of contrast agent downstream from a complete occlusion indicates lack of collateral flow.
  • the invention may take form in various components and arrangements of components, and in various steps and arrangements of steps.
  • the drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention.
  • the following generally relates to assessing collateral blood flow (which is blood flow in smaller vessels that can support a main vessel such as an artery in supplying blood to tissue) based on imaging data.
  • this includes presenting both an inflow (into a feeding artery) metric and a local tissue perfusion metric for both non-healthy tissue (e.g., diseased tissue or at risk tissue) and healthy contralateral tissue (i.e., healthy tissue of the same type) with or without the imaging data, and/or generating a collateral grading score based thereon indicative of the collateral blood flow.
  • the metrics and/or score can be used in connection with assessing an acute ischemic event and/or risk of such an event in the future.
  • the brain consists of left and right hemispheres, and inflow in both hemispheres is substantially similar and perfusion in both hemispheres is substantially similar.
  • inflow and perfusion in a healthy hemisphere can be used as a reference for inflow and perfusion in a non-healthy (e.g., diseased tissue or at risk tissue) hemisphere, such as a hemisphere affected by stroke.
  • non-healthy tissue generally refers to a hemisphere or a certain region in a hemisphere of the brain affected by stroke and healthy contralateral tissue generally refers to the other (non-affected) hemisphere or the corresponding region of the brain.
  • a region is a perfusion territory that receives its main blood supply from one distinct artery.
  • inflow and perfusion of the healthy hemisphere of the brain can be replaced or supplemented with inflow and perfusion of healthy non-brain tissue with inflow and perfusion characteristics similar to that of the inflow and perfusion characteristics of the brain.
  • collateral blood flow for other (non-brain) non-healthy tissue can be similarly assessed based on brain tissue or other tissue with inflow and perfusion characteristics similar to the inflow and perfusion characteristics of the tissue under study (the tissue of interest).
  • FIGURE 1 illustrates an example collateral flow analyzer 100.
  • the collateral flow analyzer 100 can obtain and/or receive imaging data from various imaging modalities such as computed tomography (CT), magnetic resonance (MR), positron emission tomography (PET), single photon emission computed tomography (SPECT), x-ray radiography (X-Ray), ultrasound (US), and/or other imaging modalities.
  • imaging modalities such as computed tomography (CT), magnetic resonance (MR), positron emission tomography (PET), single photon emission computed tomography (SPECT), x-ray radiography (X-Ray), ultrasound (US), and/or other imaging modalities.
  • CT computed tomography
  • MR magnetic resonance
  • PET positron emission tomography
  • SPECT single photon emission computed tomography
  • X-Ray x-ray radiography
  • US ultrasound
  • imaging data include, but are not limited to, one or more of contrast-enhanced CT data, CTA data, contrast-enhanced MRI data, MRA data, SPECT data,
  • a tissue identifier 102 identifies tissue of interest in the imaging data.
  • the illustrated tissue identifier 102 identifies such tissue based on a signal representing a predetermined tissue type selected via user input, a default parameter, a selected imaging protocol, etc.
  • the predetermined tissue type is brain tissue, for example, of a stroke patient undergoing a stroke study.
  • the predetermined tissue may include both stroke affected brain hemisphere (disease tissue or at-risk tissue) and the healthy (non stroke affected) brain hemisphere.
  • the tissue identifier 102 can employ various algorithms for identifying the tissue of interest in the imaging data. Suitable examples include, but are not limited to, automatic segmentation, semi-automatic segmentation, manual (user interactive) segmentation, model based registration (e.g., registration to atlas data), images fused with anatomical image data of the same field of view, and/or other segmentation techniques.
  • model based registration e.g., registration to atlas data
  • images fused with anatomical image data of the same field of view and/or other segmentation techniques.
  • the geometry of arteries and/or other anatomical structure and their respective perfusion territories can be determined from CTA data, MRA data, and/or other data that includes similar information.
  • a volume flow determiner 104 determines arterial blood volume inflow (Q) (and/or velocity (v)) for the identified tissue, including for both the healthy and the non-healthy (affected or at-risk) brain hemispheres. Such information can be determined from Doppler ultrasound, phase-contrast MR, other MR, interventional X-ray (e.g., blood flow estimates from arterial contrast agent concentration), and/or other imaging data.
  • the volume flow determiner 104 is omitted, and the blood inflow information is determined by and/or obtained from an apparatus or memory remote from the collateral flow determiner 104.
  • a perfusion determiner 106 determines local tissue perfusion (P), such a cerebral blood flow (CBF), for the identified tissue, including both the healthy and the non-healthy (affected or at-risk) brain hemispheres.
  • the local tissue perfusion can be determined from dynamic, contrast-enhanced CT, dynamic, contrast-enhanced MRI, non-contrast-enhanced MRI, SPECT, PET, and/or other imaging data.
  • An average local perfusion for the healthy and non-healthy tissue can be determined as a mean or median value from the corresponding segmented imaging data.
  • the perfusion determiner 106 is omitted, and local tissue perfusion information is determined by and/or obtained from an apparatus or memory remote from the collateral flow determiner 104.
  • An imaging data supplementor 108 supplements the segmented imaging data from the tissue identifier 102 and/or the imaging data with the inflow and perfusion information. In one instance, this includes generating a color map or the like with different colors corresponding to different flow and perfusion values, and the color map is overlaid or superimposed over the segmented image data and/or image data. Additionally or alternatively, a numerical value corresponding to the flow and perfusion map is overlaid or superimposed over the segmented image data and/or image data. Additionally or alternatively, other approaches for supplementing imaging data are also contemplated herein.
  • a score determiner 110 determines a collateral grading score, or a signal indicative thereof, based on the inflow and perfusion information. For the collateral grading score, the score determiner 110 computes a relative inflow metric Q contra - Q Q contra , which indicates a reduction in inflow in the non-healthy tissue relative to the healthy tissue, and a relative perfusion metric p contra - p p contra , which indicates a reduction in perfusion in the non-healthy tissue relative to the healthy tissue.
  • C 0 where the reduction in perfusion in the non-healthy tissue is proportional to the reduction in inflow in the non-healthy tissue. This indicates no or substantially no collateral flow. Where perfusion in the healthy and non-healthy tissue is the same, a score C in the range of 0 ⁇ C ⁇ 1 indicates a fraction of the inflow of the non-healthy tissue that is provided by collateral pathways.
  • the rules bank 114 may additionally or alternatively include other rules.
  • the supplemented imaging data, the supplemented segmented imaging data, the inflow metrics, the perfusion metrics, the collateral grading score, the results of the analysis, and/or other information can be provided to one or more output devices 116, including, but not limited to, a display 118, local storage 120, a data repository 122 (e.g., a RIS and/or HIS), a filmer 124, and/or other output device.
  • a display 118 including, but not limited to, a display 118, local storage 120, a data repository 122 (e.g., a RIS and/or HIS), a filmer 124, and/or other output device.
  • the display 118 can present various information.
  • the segmented imaging data for the healthy and non-healthy tissue are concurrently presented respectively along with corresponding inflow and perfusion information such as color maps, numerical values, etc.
  • Such a presentation allows a clinician to visually observe flow and perfusion information for the healthy and non-healthy tissue. This allows the clinician to compare inflow to both healthy and non-healthy tissue and perfusion of the healthy and non-healthy tissue.
  • this information indicates that the collateral flow for the non-healthy tissue is compensating for the decrease inflow.
  • the comparison depending on the inflow and perfusion data, may indicate other information.
  • a clinician can assess collateral flow of the non-healthy tissue, for example, where there is a reduction in inflow between the healthy tissue and non-healthy tissue but either no reduction in perfusion or a reduction in perfusion in the non-healthy tissue that is less than the reduction in inflow in the healthy tissue and/or for other situations.
  • the score C is presented via the display 118, providing similar information regarding the collateral flow.
  • the score provides the clinician with a value indicative of the collateral flow.
  • the result of the analysis is presented via the display 118, providing similar information regarding the collateral flow.
  • collateral flow analyzer 100 can be part of a computing system that includes one or more processors that execute computer readable instructions encoded in computer readable storage medium thereof.
  • FIGURES 2 and 3 illustrate various methods. It is to be appreciated that the acts described in the methods are for explanatory purposes and not limiting. For example, one or more of the methods may include more or less acts, including different acts. In addition, one or more acts of one or more of the methods may occur in a different order that listed. Moreover, one or more of the methods may be combined.
  • FIGURE 2 a method for assessing collateral flow based on inflow and perfusion metrics for non-healthy tissue (diseased or at-risk tissue) and healthy contralateral tissue is illustrated.
  • non-healthy (diseased or at-risk) tissue is segmented from the imaging data as described above.
  • healthy contraleral tissue is segmented from the imaging data as described above.
  • inflow and perfusion metrics are determined for the non-healthy tissue.
  • inflow and perfusion metrics are determined for the healthy contralateral tissue.
  • the inflow and perfusion metrics are presented respectively for the non-healthy and healthy contralateral tissue.
  • the inflow and perfusion metrics are superimposed or overlaid over the imaging data and/or segmented imaging data for the non-healthy and healthy contralateral tissue.
  • FIGURE 3 a method for generating a collateral grading score is illustrated.
  • FIGURE 2 a method for assessing collateral flow based on a collateral grading score determined from both inflow and perfusion metrics for non-healthy tissue (diseased or at-risk tissue) and healthy contralateral is illustrated.
  • non-healthy tissue and healthy contralateral tissue are segmented from the imaging data.
  • flow and perfusion metrics are determined for the non-healthy tissue and the healthy contralateral tissue based on the segmented imaging data.
  • a collateral grading score is computed for the non-healthy tissue based on the flow and perfusion metrics.
  • the collateral grading score provides an indication of the amount of the total inflow being provided by collateral flow.
  • the collateral grading score is presented, with or without the imaging data.
  • the acts described herein may be implemented by way of computer readable instructions, which, when executed by a computer processor(s), causes the processor(s) to carry out the acts described herein.
  • the instructions are stored in a computer readable storage medium such as memory associated with and/or otherwise accessible to the relevant computer.
  • imaging applications in which a pre-scan image is used to plan a series of image acquisitions where patient movement may result in planned FOV no longer being a desired FOV.
  • imaging applications include but are not limited to MRI, interventional X-ray, and/or other imaging applications.

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Claims (15)

  1. Procédé comprenant :
    l'obtention de mesures à la fois de premier écoulement et de première perfusion pour un tissu intéressant non sain ;
    l'obtention de mesures à la fois de deuxième écoulement et de deuxième perfusion pour un tissu intéressant sain ;
    le calcul d'une mesure d'écoulement relative sur la base des mesures d'écoulement des tissus intéressants non sain et sain ;
    le calcul d'une mesure de perfusion relative sur la base des mesures de perfusion des tissus intéressants non sain et sain ;
    la génération d'un score d'évaluation collatéral sur la base des mesures relatives d'écoulement et de perfusion ; et
    la présentation de façon concomitante des mesures à la fois de premier écoulement et de perfusion pour le tissu intéressant non sain et des mesures à la fois de deuxième écoulement et de perfusion pour le tissu intéressant sain.
  2. Procédé selon la revendication 1, dans lequel le tissu sain intéressant et le tissu non sain intéressant ont des caractéristiques d'écoulement et de perfusion essentiellement similaires.
  3. Procédé selon l'une quelconque des revendications 1 à 2, comprenant en outre :
    la présentation concomitante des mesures d'écoulement et de perfusion, respectivement, avec des données d'imagerie correspondantes pour les tissus non sain et sain intéressants.
  4. Procédé selon la revendication 3, comprenant en outre :
    la superposition des mesures à la fois de premier écoulement et de première perfusion et les données d'imagerie du tissu non sain intéressant ; et
    la superposition des mesures à la fois de deuxième écoulement et de deuxième perfusion et les données d'imagerie du tissu sain intéressant.
  5. Procédé selon la revendication 4, dans lequel les première et deuxième mesures sont superposées en tant que cartes en couleur, les couleurs correspondant à une quantité d'écoulement et de perfusion.
  6. Procédé selon l'une quelconque des revendications 1 à 5, comprenant en outre :
    la segmentation des données d'imagerie correspondant au tissu non sain intéressant et au tissu sain intéressant à partir d'un jeu de données d'imagerie.
  7. Procédé selon la revendication 6, comprenant en outre :
    la détermination des mesures d'écoulement et de perfusion sur la base des données d'imagerie segmentées.
  8. Procédé selon la revendication 1, dans lequel la mesure d'écoulement relative indique une réduction de l'écoulement dans le tissu non sain par rapport au tissu sain intéressant.
  9. Procédé selon la revendication 1, dans lequel la mesure de perfusion relative indique une réduction de la perfusion dans le tissu non sain par rapport au tissu sain intéressant.
  10. Procédé selon la revendication 1, dans lequel un score d'évaluation collatérale de zéro indique qu'une réduction de la perfusion dans le tissu non sain est proportionnelle à une réduction de l'écoulement dans le tissu non sain, indiquant ainsi essentiellement une absence de flux collatéral.
  11. Procédé selon les revendications 1 ou 10, dans lequel un score d'évaluation collatéral de l'ordre d'environ zéro à un indique un flux collatéral dans le tissu non sain.
  12. Procédé selon la revendication 11, dans lequel la valeur du score d'évaluation collatérale de l'ordre d'environ zéro à un indique une fraction d'écoulement du tissu non sain qui est assurée par des voies collatérales.
  13. Procédé selon l'une quelconque des revendications 1 à 12, dans lequel le tissu non sain est un tissu cérébral lésé ou à risque et le tissu sain est un tissu cérébral sain.
  14. Système (100), comprenant :
    un complémenteur de données d'imagerie (108) adapté pour compléter les données d'imagerie d'un tissu non sain intéressant et d'un tissu sain intéressant avec les mesures d'écoulement et de perfusion du tissu non sain intéressant et du tissu sain intéressant ; et
    un dispositif de détermination de score (110) adapté pour calculer une mesure d'écoulement relative sur la base de la mesure d'écoulement des tissus non sain et sain intéressants, et une mesure de perfusion relative sur la base de la mesure de perfusion des tissus non sain et sain intéressants et pour générer un signal indicatif d'un score d'évaluation collatérale sur la base des mesures relatives d'écoulement et de perfusion.
  15. Système (100) selon la revendication 14, dans lequel le score d'évaluation collatérale indique une fraction d'écoulement du tissu non sain qui est assurée par des voies collatérales et va de zéro, qui indique une absence de flux collatéral, à un, qui indique uniquement un flux collatéral.
EP10796141.9A 2009-12-10 2010-11-18 Evaluation de debit sanguin collateral Active EP2509500B1 (fr)

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US28520709P 2009-12-10 2009-12-10
PCT/IB2010/055265 WO2011070467A1 (fr) 2009-12-10 2010-11-18 Évaluation de débit sanguin collatéral

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CN103764036B (zh) * 2012-08-31 2016-11-16 东芝医疗系统株式会社 医用诊断图像处理装置
WO2014084382A1 (fr) * 2012-11-30 2014-06-05 株式会社 東芝 Dispositif de traitement d'images médicales
WO2016205824A1 (fr) 2015-06-19 2016-12-22 Neural Analytics, Inc. Sonde doppler transcrânienne
JP6484760B2 (ja) 2015-11-05 2019-03-13 コーニンクレッカ フィリップス エヌ ヴェKoninklijke Philips N.V. 非侵襲的血流予備量比(ffr)に対する側副血流モデル化
EP3399920B1 (fr) 2016-01-05 2020-11-04 Neural Analytics, Inc. Structure de sonde intégrée
US11589836B2 (en) 2016-01-05 2023-02-28 Novasignal Corp. Systems and methods for detecting neurological conditions
CN108778140A (zh) 2016-01-05 2018-11-09 神经系统分析公司 用于确定临床指征的系统和方法
DE102016205507A1 (de) * 2016-04-04 2017-10-05 Siemens Healthcare Gmbh Verfahren zur Ermittlung einer den Blutfluss in Kollateralen beschreibenden Kollateralinformationen, medizinische Bildaufnahmeeinrichtung, Computerprogramm und elektronisch lesbarer Datenträger
US11257584B2 (en) * 2017-08-11 2022-02-22 Elucid Bioimaging Inc. Quantitative medical imaging reporting
CN109717890A (zh) * 2018-12-28 2019-05-07 浙江大学 一种定量测定缺血性卒中患者侧枝灌注的方法

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US6792302B2 (en) * 2001-02-21 2004-09-14 Universite De Lausanne Method and apparatus for determining treatment for stroke
US6540688B1 (en) * 2001-10-11 2003-04-01 Datex-Ohmeda, Inc. Method and system for assessing collateral blood flow to a tissue region of interest
CN1689510A (zh) * 2004-04-19 2005-11-02 中国科学院自动化研究所 磁共振灌注成像的数字化方法
DE102004055460A1 (de) * 2004-11-17 2006-04-20 Siemens Ag Bildgebendes Verfahren sowie Vorrichtung zur Visualisierung von koronaren Herzkrankheiten, insbesondere von Herzinfarktschäden
US9208582B2 (en) * 2005-11-02 2015-12-08 Hitachi Medical Corporation Image analyzing system and method
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RU2012128833A (ru) 2014-01-20
JP5801316B2 (ja) 2015-10-28
CN102651997B (zh) 2015-09-09
US9125616B2 (en) 2015-09-08
US20120238888A1 (en) 2012-09-20
EP2509500A1 (fr) 2012-10-17

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